Assessing nucleotide sugar donors inside the Golgi apparatus as a prerequisite for unravelling culture impacts on glycoforms of antibodies

DOI

The dataset presented here supplements the publication titled “Assessing Nucleotide Sugar Donors Inside the Golgi Apparatus as a Prerequisite for Unraveling Culture Impacts on Glycoforms of Antibodies.” The study emphasizes the importance of glycosylation in biopharmaceuticals and unravels a novel, integrative workflow for absolute quantification of nucleotide sugar donors (NSDs) within subcellular compartments of CHO DP-12 cells. Through a combination of state-of-the-art methodologies such as subcellular fractionation, exhaustive sample extraction, and metabolomics measurements, the researchers quantified NSD concentrations, establishing a clear correlation between these metabolites and the glycan profiles observed on antibodies, especially under conditions of nutrient pulse stimulation.

The dataset enables a comprehensive and compartment-specific empirical analysis of NSD dynamics, which are essential for understanding and optimizing N-glycosylation regulation within the Golgi apparatus. This approach provides new insights into how glycosylation can be controlled and enhanced in production cell lines, with the ultimate aim of improving the efficiency and consistency of glycosylation in biotherapeutic production.

The data consists of absolute and relative quantifications, including mean values and standard deviations/errors from wet lab measurements. These encompass concentrations of fractionated proteins and metabolites, along with cultivation data such as cell counts, substrate/product/byproduct concentrations, and cell viability metrics over time. Additionally, the dataset provides quantitative data on antibody production and the relative abundance ratios of glycoforms under various nutrient conditions. Graphic representations of western blot analyses and other experimental results are included to support the quantitative findings. This dataset serves as a valuable resource for researchers aiming to optimize glycosylation processes in biopharmaceutical production systems, especially by embodying a new generation of metabolic data with subcellular precision for modelling purposes.

Glycosylation is a critical quality attribute in biopharmaceuticals that influences cru-cial properties, such as immunogenicity and stability. Current methods for model-ing glycosylation typically rely on imprecise or limited data on nucleotide sugar do-nor (NSD) dynamics. These methods use in vitro transporter kinetics or flux balance analysis, which overlook the key aspects of metabolic regulation. We devised an integrative workflow for absolute subcellular NSD quantification in both cytoplasm and secretory organelles. Using subcellular fractionation, exhaustive sample extrac-tion, and liquid chromatography triple-quadrupole tandem mass spectrometry (LC-QQQ MS/MS), we accurately measured NSD concentrations ranging 1.6 amol/cell to 3 fmol/cell. Our NSD concentration profiles aligned closely with the glycan distributions on anti-bodies, particularly after nutrient pulsing to stimulate NSD production. This method enables empirical observation of compartment-specific NSD dynamics. Thus, this study provides novel insights indicating that N-glycosylation, which governs NSD supply, is primarily regulated within the Golgi apparatus (GA). This method offers a novel tool to obtain sophisticated data for the more efficient optimization of glycosyl-ation processes in production cell lines.

Identifier
DOI https://doi.org/10.18419/darus-4541
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/darus-4541
Provenance
Creator Regett, Niklas ORCID logo; Marcel Dieterle; Fleur Peters ORCID logo; Max Deuring; Kaja Stegmaier; Teleki, Attila ORCID logo; Takors, Ralf ORCID logo
Publisher DaRUS
Contributor Takors, Ralf
Publication Year 2024
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Takors, Ralf (Universität Stuttgart)
Representation
Resource Type Dataset
Format application/vnd.openxmlformats-officedocument.spreadsheetml.sheet; text/tab-separated-values
Size 10400; 12630; 797; 2531; 13524; 1284; 566; 10500; 684; 260; 144
Version 1.0
Discipline Biological Process Engineering; Construction Engineering and Architecture; Engineering; Engineering Sciences; Life Sciences; Medicine; Process Engineering, Technical Chemistry; Thermal Engineering/Process Engineering